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. In this project, you’ll have the opportunity to be trained and become a proficient user of a range of advanced experimental techniques. For instance, you’ll learn how to use in-situ X-ray Computed
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understanding of engineering mechanics and mechanical behaviour of materials. Knowledge of irradiation damage, computer modelling for nuclear materials, or steel metallurgy would be advantageous. Potential
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computational mechanics or multiphysics modeling, with particular interest in fracture mechanics and chemo-mechanical degradation. Knowledge of solid-state defect chemistry (advantageous). You will join a dynamic
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focuses on AI-driven fault diagnosis, predictive analytics, and embedded self-healing mechanisms, with applications in aerospace, robotics, smart energy, and industrial automation. Based
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at Imperial as part of this initiative, in the general area of Mechanics and Characterisation of Next Generation EAF Recycled Steels for Forming and Welding Applications, leading to the award of a PhD degree
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. The project focuses on power-aware computing, thermal optimization, and sustainable electronic design, targeting critical applications in aerospace, healthcare, and industrial automation. Hosted by the renowned
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university tuition fees. How to Apply: All applications should be made online . Under ‘Campus’, please select ‘Loughborough’ and select ‘Mechanical and Manufacturing Engineering’ under ‘Programme’. Please
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their swimming dynamics and the mechanical deformations caused by the encapsulated active biomolecules, you will explore ways to control their motion in 3D space. Synthetic microswimmers have many potential
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£20,780 per year, and includes a 3-month fusion engineering CDT training programme as part of the 2026 Cohort. This project is co-supervised by Dr Chris Hardie from UKAEA. The UoB Materials for eXtremes
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace - In Partnership with Rolls-Royce PhD
knowledge graphs for predictive insights. Design feedback mechanisms to deliver interpretable outputs such as alerts, recommendations, and confidence scores. Validate system robustness using real-world